All Classes and Interfaces

Class
Description
 
A tuple that describes a range of the number line between 0 and 1.
 
Feature cache metadata.
 
 
Cache behavior modes for the SDK.
Derived feature cache state.
Client lifecycle metadata.
 
INTERNAL: Implementation of condition evaluation
Sanitized SDK configuration metadata.
 
Builds sanitized configuration diagnostics without exposing SDK secrets.
A data type class used internally to help evaluate conditions
INTERNAL: This class is used internally to decrypt an encrypted features response
 
Read-only snapshot of the current SDK state.
 
Runtime context used while collecting a diagnostics snapshot.
 
Derives a compact health summary from diagnostics sections.
Derived high-level SDK health state.
Actionable diagnostics issue derived from the raw SDK state snapshot.
 
Stable machine-readable diagnostics issue codes.
Diagnostics issue severity levels.
Provides read-only diagnostic snapshots.
Masks known diagnostics secrets before they can be exposed in support dumps.
Collected diagnostics sections before the final public diagnostics object is assembled.
 
Sanitized error metadata for diagnostics output.
 
Maps internal exceptions into sanitized diagnostics output.
 
 
Defines a single Experiment
 
INTERNAL: Implementation of experiment evaluation
 
The result of an GrowthBook.run(Experiment) call
 
A callback to be executed with an ExperimentResult whenever an experiment is run.
A thread-safe LRU Cache implementation to keep track of the most recent experiments.
The feature with a generic value type.
Thrown when a configured feature cache cannot be accessed.
Source used to report feature diagnostics.
Current feature state metadata.
 
Builds feature diagnostics from repository-visible feature state.
INTERNAL: Implementation of feature evaluation.
This error is thrown by GBFeaturesRepository You can call getErrorCode() to get an enum of various error types you can handle.
Error codes available for a FeatureFetchException
Applies the shared failure behavior after feature fetch retries are exhausted.
Classifies feature fetch HTTP responses for retry behavior.
Executes feature fetch attempts with a bounded retry policy.
Unit of feature fetch work that can be retried by this executor.
Configures bounded exponential backoff for feature fetch requests.
A type-safe reference to a feature flag.
Diagnostics metadata for feature keys in the current snapshot.
 
Decides whether a non-forced feature refresh can skip the network request because cached or in-memory feature data is still fresh enough.
Owns refresh execution mode selection and background refresh scheduling.
 
Enum that used in strategy for building url
 
Results for a FeatureEvaluator.evaluateFeature(String, EvaluationContext, Class) value (any) - The assigned value of the feature on (boolean) - The assigned value cast to a boolean off (boolean) - The assigned value cast to a boolean and then negated source (enum) - One of "unknownFeature", "defaultValue", "force", or "experiment" experiment (Experiment or null) - When source is "experiment", this will be an Experiment object experimentResult (ExperimentResult or null) - When source is "experiment", this will be an ExperimentResult object
 
An enum of the possible sources for the feature result
Overrides the defaultValue of a Feature based on a set of requirements.
 
Derived feature data state.
Listen for feature usage events
 
 
Class responsible for caching data to a file
Object used for mutual exclusion and filtering users out of experiments based on random hashes.
 
Normalizes forced variation values from external inputs into integer variation IDs.
 
Context object passed into the GrowthBook constructor.
The builder class to help create a context.
This class can be created with its `builder()` or constructor.
 
Appends User-Agent info to the request headers.
Model that created for generating StickyBucketAssignmentDocModel
 
 
GrowthBook SDK class.
 
Provides read-only diagnostic snapshots from a multi-user GrowthBookClient.
Read-only view over the client state required to build diagnostics snapshots.
 
INTERNAL: This convenience class was created to help with the serialization and deserialization of custom types.
A plugin that can observe experiment and feature evaluations on a GrowthBook instance.
Batches experiment/feature evaluation events and POSTs them to the GrowthBook data-warehouse ingest endpoint.
INTERNAL: Implementation of for internal utility methods to support GrowthBook
Model for care a pair of hashAttribute and hashValue
High-level health summary derived from all diagnostics sections.
 
 
 
INTERNAL: Interface that is used internally for the GBFeaturesRepository
Simple process-lifetime in-memory cache manager.
For simple bucket persistence using the in memory's storage(Map) (can be polyfilled for other environments)
Thrown when GrowthBook options fail start-up validation.
 
 
 
Deprecated.
 
This class can be created with its `builder()` or constructor.
 
Operator for use in the condition JSON
 
 
 
Validates Options once, at client start-up, so misconfigurations are reported up front with a clear message instead of surfacing later as an opaque fetch failure.
A ParentCondition defines a prerequisite.
Holds a set of GrowthBookPlugins registered with a GrowthBook instance and dispatches lifecycle/event callbacks to each one.
Feature refresh metadata.
 
Controls whether a feature refresh may use cache freshness checks.
In-memory cache for remote-eval responses.
Builds deterministic cache keys for remote evaluation payloads.
Remote evaluation metadata.
 
Endpoint helpers for the GrowthBook remote-eval API.
Validates SDK options before enabling remote evaluation.
Builds the remote-eval request payload in the JS/Python SDK wire format.
Parsed response returned by the GrowthBook remote evaluation endpoint.
Parses the proxy response used by remote evaluation.
HTTP client for the remote evaluation endpoint.
 
 
Shared SDK constants used across repository, refresh, and diagnostics code.
 
SDK build metadata.
 
Identifying metadata for this SDK.
 
 
StickyAssignmentsDocument class is presenting a model for accumulate such data as: attributeName, attributeValue and assignments
Sticky Bucket Service is responsible for persisting previously seen variations and ensure that the user experience remains consistent for your users.
Model for caring data: variation and versionIsBlocked
Streaming refresh connection metadata.
 
Derived streaming connection state.
Classifies raw streaming signals into a single diagnostics state.
Raw streaming signals gathered from the active repository or remote-eval coordinator.
 
 
 
Used for remote feature evaluation to trigger the TrackingCallback
This callback is called with the Experiment and ExperimentResult when an experiment is evaluated.
 
 
Configuration for GrowthBookTrackingPlugin.
 
 
Default immutable implementation of FeatureKey.
 
 
 
Meta info about an experiment variation
 
This class contains SDK version information.